import torch.utils.data
import torchvision
from torch.utils.tensorboard import SummaryWriter

test_train = torchvision.datasets.CIFAR10("./datavision",train=False,transform=torchvision.transforms.ToTensor(),)
test_loader = torch.utils.data.DataLoader(test_train,batch_size=64,shuffle=True,num_workers=0,drop_last=False)
img,target = test_train[0]
#print(img,"\n",target)
writer = SummaryWriter("log2")
for epoch in range(3):
    step = 0
    for data in test_loader:
        imgs,targets = data
        #print(imgs.shape,"\n",targets)
        writer.add_images(f"loader{epoch}",imgs,step)
        step += 1
writer.close()
